Overview

Dataset statistics

Number of variables40
Number of observations246022
Missing cells0
Missing cells (%)0.0%
Duplicate rows9
Duplicate rows (%)< 0.1%
Total size in memory75.1 MiB
Average record size in memory320.0 B

Variable types

Text1
Categorical11
Numeric6
Boolean22

Alerts

Dataset has 9 (< 0.1%) duplicate rowsDuplicates
HadHeartAttack is highly imbalanced (69.4%)Imbalance
HadAngina is highly imbalanced (66.9%)Imbalance
HadStroke is highly imbalanced (75.3%)Imbalance
HadSkinCancer is highly imbalanced (57.9%)Imbalance
HadCOPD is highly imbalanced (60.8%)Imbalance
HadKidneyDisease is highly imbalanced (73.1%)Imbalance
HadDiabetes is highly imbalanced (60.5%)Imbalance
DeafOrHardOfHearing is highly imbalanced (57.9%)Imbalance
BlindOrVisionDifficulty is highly imbalanced (71.5%)Imbalance
DifficultyConcentrating is highly imbalanced (51.0%)Imbalance
DifficultyDressingBathing is highly imbalanced (78.6%)Imbalance
DifficultyErrands is highly imbalanced (64.7%)Imbalance
ECigaretteUsage is highly imbalanced (50.0%)Imbalance
HighRiskLastYear is highly imbalanced (74.4%)Imbalance
PhysicalHealthDays has 152802 (62.1%) zerosZeros
MentalHealthDays has 150454 (61.2%) zerosZeros

Reproduction

Analysis started2024-04-16 19:55:46.646547
Analysis finished2024-04-16 19:56:10.175130
Duration23.53 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

State
Text

Distinct54
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:10.403532image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Length

Max length20
Median length12
Mean length8.3265399
Min length4

Characters and Unicode

Total characters2048512
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlabama
2nd rowAlabama
3rd rowAlabama
4th rowAlabama
5th rowAlabama
ValueCountFrequency (%)
new 19614
 
6.7%
washington 15000
 
5.1%
south 9876
 
3.4%
maryland 9165
 
3.1%
minnesota 9161
 
3.1%
ohio 8995
 
3.1%
york 8923
 
3.0%
virginia 8539
 
2.9%
carolina 8022
 
2.7%
texas 7408
 
2.5%
Other values (50) 189726
64.4%
2024-04-16T16:56:10.885151image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 265537
13.0%
i 196983
 
9.6%
n 183533
 
9.0%
o 174605
 
8.5%
s 141121
 
6.9%
e 117147
 
5.7%
r 103779
 
5.1%
t 93933
 
4.6%
h 68405
 
3.3%
l 58483
 
2.9%
Other values (36) 644986
31.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2048512
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 265537
13.0%
i 196983
 
9.6%
n 183533
 
9.0%
o 174605
 
8.5%
s 141121
 
6.9%
e 117147
 
5.7%
r 103779
 
5.1%
t 93933
 
4.6%
h 68405
 
3.3%
l 58483
 
2.9%
Other values (36) 644986
31.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2048512
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 265537
13.0%
i 196983
 
9.6%
n 183533
 
9.0%
o 174605
 
8.5%
s 141121
 
6.9%
e 117147
 
5.7%
r 103779
 
5.1%
t 93933
 
4.6%
h 68405
 
3.3%
l 58483
 
2.9%
Other values (36) 644986
31.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2048512
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 265537
13.0%
i 196983
 
9.6%
n 183533
 
9.0%
o 174605
 
8.5%
s 141121
 
6.9%
e 117147
 
5.7%
r 103779
 
5.1%
t 93933
 
4.6%
h 68405
 
3.3%
l 58483
 
2.9%
Other values (36) 644986
31.5%

Sex
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Female
127811 
Male
118211 

Length

Max length6
Median length6
Mean length5.0390209
Min length4

Characters and Unicode

Total characters1239710
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowMale
3rd rowMale
4th rowFemale
5th rowFemale

Common Values

ValueCountFrequency (%)
Female 127811
52.0%
Male 118211
48.0%

Length

2024-04-16T16:56:11.073530image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:11.206480image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
female 127811
52.0%
male 118211
48.0%

Most occurring characters

ValueCountFrequency (%)
e 373833
30.2%
a 246022
19.8%
l 246022
19.8%
F 127811
 
10.3%
m 127811
 
10.3%
M 118211
 
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1239710
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 373833
30.2%
a 246022
19.8%
l 246022
19.8%
F 127811
 
10.3%
m 127811
 
10.3%
M 118211
 
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1239710
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 373833
30.2%
a 246022
19.8%
l 246022
19.8%
F 127811
 
10.3%
m 127811
 
10.3%
M 118211
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1239710
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 373833
30.2%
a 246022
19.8%
l 246022
19.8%
F 127811
 
10.3%
m 127811
 
10.3%
M 118211
 
9.5%

GeneralHealth
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Very good
86999 
Good
77409 
Excellent
41525 
Fair
30659 
Poor
9430 

Length

Max length9
Median length9
Mean length6.6120428
Min length4

Characters and Unicode

Total characters1626708
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowVery good
2nd rowVery good
3rd rowVery good
4th rowFair
5th rowGood

Common Values

ValueCountFrequency (%)
Very good 86999
35.4%
Good 77409
31.5%
Excellent 41525
16.9%
Fair 30659
 
12.5%
Poor 9430
 
3.8%

Length

2024-04-16T16:56:11.335550image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:11.468418image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
good 164408
49.4%
very 86999
26.1%
excellent 41525
 
12.5%
fair 30659
 
9.2%
poor 9430
 
2.8%

Most occurring characters

ValueCountFrequency (%)
o 347676
21.4%
e 170049
10.5%
d 164408
10.1%
r 127088
 
7.8%
V 86999
 
5.3%
y 86999
 
5.3%
86999
 
5.3%
g 86999
 
5.3%
l 83050
 
5.1%
G 77409
 
4.8%
Other values (9) 309032
19.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1626708
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 347676
21.4%
e 170049
10.5%
d 164408
10.1%
r 127088
 
7.8%
V 86999
 
5.3%
y 86999
 
5.3%
86999
 
5.3%
g 86999
 
5.3%
l 83050
 
5.1%
G 77409
 
4.8%
Other values (9) 309032
19.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1626708
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 347676
21.4%
e 170049
10.5%
d 164408
10.1%
r 127088
 
7.8%
V 86999
 
5.3%
y 86999
 
5.3%
86999
 
5.3%
g 86999
 
5.3%
l 83050
 
5.1%
G 77409
 
4.8%
Other values (9) 309032
19.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1626708
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 347676
21.4%
e 170049
10.5%
d 164408
10.1%
r 127088
 
7.8%
V 86999
 
5.3%
y 86999
 
5.3%
86999
 
5.3%
g 86999
 
5.3%
l 83050
 
5.1%
G 77409
 
4.8%
Other values (9) 309032
19.0%

PhysicalHealthDays
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1190259
Minimum0
Maximum30
Zeros152802
Zeros (%)62.1%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:11.625413image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile30
Maximum30
Range30
Interquartile range (IQR)3

Descriptive statistics

Standard deviation8.4058438
Coefficient of variation (CV)2.0407358
Kurtosis3.9728649
Mean4.1190259
Median Absolute Deviation (MAD)0
Skewness2.2843046
Sum1013371
Variance70.65821
MonotonicityNot monotonic
2024-04-16T16:56:11.801854image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 152802
62.1%
30 17160
 
7.0%
2 14728
 
6.0%
1 10058
 
4.1%
3 9137
 
3.7%
5 8939
 
3.6%
10 6068
 
2.5%
7 5221
 
2.1%
4 4906
 
2.0%
15 4845
 
2.0%
Other values (21) 12158
 
4.9%
ValueCountFrequency (%)
0 152802
62.1%
1 10058
 
4.1%
2 14728
 
6.0%
3 9137
 
3.7%
4 4906
 
2.0%
5 8939
 
3.6%
6 1421
 
0.6%
7 5221
 
2.1%
8 961
 
0.4%
9 211
 
0.1%
ValueCountFrequency (%)
30 17160
7.0%
29 178
 
0.1%
28 365
 
0.1%
27 103
 
< 0.1%
26 64
 
< 0.1%
25 1123
 
0.5%
24 60
 
< 0.1%
23 54
 
< 0.1%
22 72
 
< 0.1%
21 584
 
0.2%

MentalHealthDays
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1671395
Minimum0
Maximum30
Zeros150454
Zeros (%)61.2%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:11.956875image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile30
Maximum30
Range30
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.1026871
Coefficient of variation (CV)1.9444242
Kurtosis3.8587287
Mean4.1671395
Median Absolute Deviation (MAD)0
Skewness2.2152689
Sum1025208
Variance65.653539
MonotonicityNot monotonic
2024-04-16T16:56:12.114027image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 150454
61.2%
2 13810
 
5.6%
30 13702
 
5.6%
5 11623
 
4.7%
3 8849
 
3.6%
10 8831
 
3.6%
1 8244
 
3.4%
15 8061
 
3.3%
20 4925
 
2.0%
4 4568
 
1.9%
Other values (21) 12955
 
5.3%
ValueCountFrequency (%)
0 150454
61.2%
1 8244
 
3.4%
2 13810
 
5.6%
3 8849
 
3.6%
4 4568
 
1.9%
5 11623
 
4.7%
6 1326
 
0.5%
7 4485
 
1.8%
8 973
 
0.4%
9 145
 
0.1%
ValueCountFrequency (%)
30 13702
5.6%
29 261
 
0.1%
28 484
 
0.2%
27 113
 
< 0.1%
26 59
 
< 0.1%
25 1647
 
0.7%
24 68
 
< 0.1%
23 51
 
< 0.1%
22 101
 
< 0.1%
21 301
 
0.1%

LastCheckupTime
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Within past year (anytime less than 12 months ago)
198153 
Within past 2 years (1 year but less than 2 years ago)
23227 
Within past 5 years (2 years but less than 5 years ago)
 
13744
5 or more years ago
 
10898

Length

Max length55
Median length50
Mean length49.283763
Min length19

Characters and Unicode

Total characters12124890
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWithin past year (anytime less than 12 months ago)
2nd rowWithin past year (anytime less than 12 months ago)
3rd rowWithin past year (anytime less than 12 months ago)
4th rowWithin past year (anytime less than 12 months ago)
5th rowWithin past year (anytime less than 12 months ago)

Common Values

ValueCountFrequency (%)
Within past year (anytime less than 12 months ago) 198153
80.5%
Within past 2 years (1 year but less than 2 years ago) 23227
 
9.4%
Within past 5 years (2 years but less than 5 years ago) 13744
 
5.6%
5 or more years ago 10898
 
4.4%

Length

2024-04-16T16:56:12.287898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:12.415840image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
ago 246022
10.8%
within 235124
10.3%
past 235124
10.3%
less 235124
10.3%
than 235124
10.3%
year 221380
9.7%
anytime 198153
8.7%
12 198153
8.7%
months 198153
8.7%
years 98584
4.3%
Other values (6) 180578
7.9%

Most occurring characters

ValueCountFrequency (%)
2035497
16.8%
a 1234387
10.2%
t 1138649
9.4%
s 1002109
 
8.3%
n 866554
 
7.1%
e 764139
 
6.3%
h 668401
 
5.5%
i 668401
 
5.5%
y 518117
 
4.3%
o 465971
 
3.8%
Other values (13) 2762665
22.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12124890
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2035497
16.8%
a 1234387
10.2%
t 1138649
9.4%
s 1002109
 
8.3%
n 866554
 
7.1%
e 764139
 
6.3%
h 668401
 
5.5%
i 668401
 
5.5%
y 518117
 
4.3%
o 465971
 
3.8%
Other values (13) 2762665
22.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12124890
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2035497
16.8%
a 1234387
10.2%
t 1138649
9.4%
s 1002109
 
8.3%
n 866554
 
7.1%
e 764139
 
6.3%
h 668401
 
5.5%
i 668401
 
5.5%
y 518117
 
4.3%
o 465971
 
3.8%
Other values (13) 2762665
22.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12124890
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2035497
16.8%
a 1234387
10.2%
t 1138649
9.4%
s 1002109
 
8.3%
n 866554
 
7.1%
e 764139
 
6.3%
h 668401
 
5.5%
i 668401
 
5.5%
y 518117
 
4.3%
o 465971
 
3.8%
Other values (13) 2762665
22.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
True
191318 
False
54704 
ValueCountFrequency (%)
True 191318
77.8%
False 54704
 
22.2%
2024-04-16T16:56:12.545316image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

SleepHours
Real number (ℝ)

Distinct23
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0213314
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:12.689136image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q16
median7
Q38
95-th percentile9
Maximum24
Range23
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4406814
Coefficient of variation (CV)0.20518635
Kurtosis7.2068297
Mean7.0213314
Median Absolute Deviation (MAD)1
Skewness0.56143668
Sum1727402
Variance2.0755629
MonotonicityNot monotonic
2024-04-16T16:56:12.833627image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
7 76447
31.1%
8 69927
28.4%
6 53981
21.9%
5 16417
 
6.7%
9 11859
 
4.8%
4 6478
 
2.6%
10 5468
 
2.2%
3 1618
 
0.7%
12 1476
 
0.6%
2 740
 
0.3%
Other values (13) 1611
 
0.7%
ValueCountFrequency (%)
1 563
 
0.2%
2 740
 
0.3%
3 1618
 
0.7%
4 6478
 
2.6%
5 16417
 
6.7%
6 53981
21.9%
7 76447
31.1%
8 69927
28.4%
9 11859
 
4.8%
10 5468
 
2.2%
ValueCountFrequency (%)
24 13
 
< 0.1%
23 6
 
< 0.1%
22 5
 
< 0.1%
20 50
 
< 0.1%
19 5
 
< 0.1%
18 83
< 0.1%
17 11
 
< 0.1%
16 155
0.1%
15 154
0.1%
14 148
0.1%

RemovedTeeth
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
None of them
131592 
1 to 5
74702 
6 or more, but not all
25950 
All
13778 

Length

Max length22
Median length12
Mean length10.728919
Min length3

Characters and Unicode

Total characters2639550
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNone of them
2nd rowNone of them
3rd row6 or more, but not all
4th rowNone of them
5th row1 to 5

Common Values

ValueCountFrequency (%)
None of them 131592
53.5%
1 to 5 74702
30.4%
6 or more, but not all 25950
 
10.5%
All 13778
 
5.6%

Length

2024-04-16T16:56:12.998463image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:13.269006image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
none 131592
16.7%
of 131592
16.7%
them 131592
16.7%
1 74702
9.5%
to 74702
9.5%
5 74702
9.5%
all 39728
 
5.0%
6 25950
 
3.3%
or 25950
 
3.3%
more 25950
 
3.3%
Other values (2) 51900
 
6.6%

Most occurring characters

ValueCountFrequency (%)
542338
20.5%
o 415736
15.8%
e 289134
11.0%
t 258194
9.8%
n 157542
 
6.0%
m 157542
 
6.0%
N 131592
 
5.0%
f 131592
 
5.0%
h 131592
 
5.0%
l 79456
 
3.0%
Other values (9) 344832
13.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2639550
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
542338
20.5%
o 415736
15.8%
e 289134
11.0%
t 258194
9.8%
n 157542
 
6.0%
m 157542
 
6.0%
N 131592
 
5.0%
f 131592
 
5.0%
h 131592
 
5.0%
l 79456
 
3.0%
Other values (9) 344832
13.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2639550
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
542338
20.5%
o 415736
15.8%
e 289134
11.0%
t 258194
9.8%
n 157542
 
6.0%
m 157542
 
6.0%
N 131592
 
5.0%
f 131592
 
5.0%
h 131592
 
5.0%
l 79456
 
3.0%
Other values (9) 344832
13.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2639550
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
542338
20.5%
o 415736
15.8%
e 289134
11.0%
t 258194
9.8%
n 157542
 
6.0%
m 157542
 
6.0%
N 131592
 
5.0%
f 131592
 
5.0%
h 131592
 
5.0%
l 79456
 
3.0%
Other values (9) 344832
13.1%

HadHeartAttack
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
232587 
True
 
13435
ValueCountFrequency (%)
False 232587
94.5%
True 13435
 
5.5%
2024-04-16T16:56:13.387466image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadAngina
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
231069 
True
 
14953
ValueCountFrequency (%)
False 231069
93.9%
True 14953
 
6.1%
2024-04-16T16:56:13.485125image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadStroke
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
235910 
True
 
10112
ValueCountFrequency (%)
False 235910
95.9%
True 10112
 
4.1%
2024-04-16T16:56:13.582258image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadAsthma
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
209493 
True
36529 
ValueCountFrequency (%)
False 209493
85.2%
True 36529
 
14.8%
2024-04-16T16:56:13.704411image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadSkinCancer
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
225001 
True
 
21021
ValueCountFrequency (%)
False 225001
91.5%
True 21021
 
8.5%
2024-04-16T16:56:13.814983image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadCOPD
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
227028 
True
 
18994
ValueCountFrequency (%)
False 227028
92.3%
True 18994
 
7.7%
2024-04-16T16:56:13.918686image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
195402 
True
50620 
ValueCountFrequency (%)
False 195402
79.4%
True 50620
 
20.6%
2024-04-16T16:56:14.022122image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadKidneyDisease
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
234738 
True
 
11284
ValueCountFrequency (%)
False 234738
95.4%
True 11284
 
4.6%
2024-04-16T16:56:14.124079image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
161139 
True
84883 
ValueCountFrequency (%)
False 161139
65.5%
True 84883
34.5%
2024-04-16T16:56:14.228249image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HadDiabetes
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
No
204834 
Yes
33813 
No, pre-diabetes or borderline diabetes
 
5392
Yes, but only during pregnancy (female)
 
1983

Length

Max length39
Median length2
Mean length3.2465877
Min length2

Characters and Unicode

Total characters798732
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 204834
83.3%
Yes 33813
 
13.7%
No, pre-diabetes or borderline diabetes 5392
 
2.2%
Yes, but only during pregnancy (female) 1983
 
0.8%

Length

2024-04-16T16:56:14.365268image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:14.501958image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
no 210226
75.8%
yes 35796
 
12.9%
pre-diabetes 5392
 
1.9%
or 5392
 
1.9%
borderline 5392
 
1.9%
diabetes 5392
 
1.9%
but 1983
 
0.7%
only 1983
 
0.7%
during 1983
 
0.7%
pregnancy 1983
 
0.7%

Most occurring characters

ValueCountFrequency (%)
o 222993
27.9%
N 210226
26.3%
e 79489
 
10.0%
s 46580
 
5.8%
Y 35796
 
4.5%
31483
 
3.9%
r 25534
 
3.2%
d 18159
 
2.3%
b 18159
 
2.3%
i 18159
 
2.3%
Other values (15) 92154
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 798732
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 222993
27.9%
N 210226
26.3%
e 79489
 
10.0%
s 46580
 
5.8%
Y 35796
 
4.5%
31483
 
3.9%
r 25534
 
3.2%
d 18159
 
2.3%
b 18159
 
2.3%
i 18159
 
2.3%
Other values (15) 92154
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 798732
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 222993
27.9%
N 210226
26.3%
e 79489
 
10.0%
s 46580
 
5.8%
Y 35796
 
4.5%
31483
 
3.9%
r 25534
 
3.2%
d 18159
 
2.3%
b 18159
 
2.3%
i 18159
 
2.3%
Other values (15) 92154
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 798732
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 222993
27.9%
N 210226
26.3%
e 79489
 
10.0%
s 46580
 
5.8%
Y 35796
 
4.5%
31483
 
3.9%
r 25534
 
3.2%
d 18159
 
2.3%
b 18159
 
2.3%
i 18159
 
2.3%
Other values (15) 92154
11.5%

DeafOrHardOfHearing
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
224990 
True
 
21032
ValueCountFrequency (%)
False 224990
91.5%
True 21032
 
8.5%
2024-04-16T16:56:14.628586image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

BlindOrVisionDifficulty
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
233796 
True
 
12226
ValueCountFrequency (%)
False 233796
95.0%
True 12226
 
5.0%
2024-04-16T16:56:14.759996image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

DifficultyConcentrating
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
219802 
True
26220 
ValueCountFrequency (%)
False 219802
89.3%
True 26220
 
10.7%
2024-04-16T16:56:14.863415image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
209952 
True
36070 
ValueCountFrequency (%)
False 209952
85.3%
True 36070
 
14.7%
2024-04-16T16:56:14.966887image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

DifficultyDressingBathing
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
237682 
True
 
8340
ValueCountFrequency (%)
False 237682
96.6%
True 8340
 
3.4%
2024-04-16T16:56:15.063445image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

DifficultyErrands
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
229638 
True
 
16384
ValueCountFrequency (%)
False 229638
93.3%
True 16384
 
6.7%
2024-04-16T16:56:15.158003image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

SmokerStatus
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Never smoked
147737 
Former smoker
68527 
Current smoker - now smokes every day
21659 
Current smoker - now smokes some days
 
8099

Length

Max length37
Median length12
Mean length15.302457
Min length12

Characters and Unicode

Total characters3764741
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFormer smoker
2nd rowFormer smoker
3rd rowFormer smoker
4th rowNever smoked
5th rowNever smoked

Common Values

ValueCountFrequency (%)
Never smoked 147737
60.1%
Former smoker 68527
27.9%
Current smoker - now smokes every day 21659
 
8.8%
Current smoker - now smokes some days 8099
 
3.3%

Length

2024-04-16T16:56:15.279014image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:15.399552image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
never 147737
23.1%
smoked 147737
23.1%
smoker 98285
15.3%
former 68527
10.7%
current 29758
 
4.6%
29758
 
4.6%
now 29758
 
4.6%
smokes 29758
 
4.6%
every 21659
 
3.4%
day 21659
 
3.4%
Other values (2) 16198
 
2.5%

Most occurring characters

ValueCountFrequency (%)
e 720956
19.2%
r 464251
12.3%
394812
10.5%
o 382164
10.2%
m 352406
9.4%
s 321736
8.5%
k 275780
 
7.3%
d 177495
 
4.7%
v 169396
 
4.5%
N 147737
 
3.9%
Other values (9) 358008
9.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3764741
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 720956
19.2%
r 464251
12.3%
394812
10.5%
o 382164
10.2%
m 352406
9.4%
s 321736
8.5%
k 275780
 
7.3%
d 177495
 
4.7%
v 169396
 
4.5%
N 147737
 
3.9%
Other values (9) 358008
9.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3764741
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 720956
19.2%
r 464251
12.3%
394812
10.5%
o 382164
10.2%
m 352406
9.4%
s 321736
8.5%
k 275780
 
7.3%
d 177495
 
4.7%
v 169396
 
4.5%
N 147737
 
3.9%
Other values (9) 358008
9.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3764741
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 720956
19.2%
r 464251
12.3%
394812
10.5%
o 382164
10.2%
m 352406
9.4%
s 321736
8.5%
k 275780
 
7.3%
d 177495
 
4.7%
v 169396
 
4.5%
N 147737
 
3.9%
Other values (9) 358008
9.5%

ECigaretteUsage
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Never used e-cigarettes in my entire life
190128 
Not at all (right now)
43281 
Use them some days
 
6658
Use them every day
 
5955

Length

Max length41
Median length41
Mean length36.478299
Min length18

Characters and Unicode

Total characters8974464
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNever used e-cigarettes in my entire life
2nd rowNever used e-cigarettes in my entire life
3rd rowNever used e-cigarettes in my entire life
4th rowNever used e-cigarettes in my entire life
5th rowNever used e-cigarettes in my entire life

Common Values

ValueCountFrequency (%)
Never used e-cigarettes in my entire life 190128
77.3%
Not at all (right now) 43281
 
17.6%
Use them some days 6658
 
2.7%
Use them every day 5955
 
2.4%

Length

2024-04-16T16:56:15.585570image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:15.747760image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
never 190128
11.9%
used 190128
11.9%
e-cigarettes 190128
11.9%
in 190128
11.9%
my 190128
11.9%
entire 190128
11.9%
life 190128
11.9%
now 43281
 
2.7%
right 43281
 
2.7%
all 43281
 
2.7%
Other values (8) 137014
8.6%

Most occurring characters

ValueCountFrequency (%)
e 1754946
19.6%
1351731
15.1%
i 803793
 
9.0%
t 712840
 
7.9%
r 619620
 
6.9%
n 423537
 
4.7%
s 406185
 
4.5%
a 289303
 
3.2%
l 276690
 
3.1%
g 233409
 
2.6%
Other values (15) 2102410
23.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8974464
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1754946
19.6%
1351731
15.1%
i 803793
 
9.0%
t 712840
 
7.9%
r 619620
 
6.9%
n 423537
 
4.7%
s 406185
 
4.5%
a 289303
 
3.2%
l 276690
 
3.1%
g 233409
 
2.6%
Other values (15) 2102410
23.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8974464
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1754946
19.6%
1351731
15.1%
i 803793
 
9.0%
t 712840
 
7.9%
r 619620
 
6.9%
n 423537
 
4.7%
s 406185
 
4.5%
a 289303
 
3.2%
l 276690
 
3.1%
g 233409
 
2.6%
Other values (15) 2102410
23.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8974464
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1754946
19.6%
1351731
15.1%
i 803793
 
9.0%
t 712840
 
7.9%
r 619620
 
6.9%
n 423537
 
4.7%
s 406185
 
4.5%
a 289303
 
3.2%
l 276690
 
3.1%
g 233409
 
2.6%
Other values (15) 2102410
23.4%

ChestScan
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
141822 
True
104200 
ValueCountFrequency (%)
False 141822
57.6%
True 104200
42.4%
2024-04-16T16:56:15.885272image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
White only, Non-Hispanic
186336 
Hispanic
22570 
Black only, Non-Hispanic
19330 
Other race only, Non-Hispanic
 
12205
Multiracial, Non-Hispanic
 
5581

Length

Max length29
Median length24
Mean length22.802896
Min length8

Characters and Unicode

Total characters5610014
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWhite only, Non-Hispanic
2nd rowWhite only, Non-Hispanic
3rd rowWhite only, Non-Hispanic
4th rowWhite only, Non-Hispanic
5th rowWhite only, Non-Hispanic

Common Values

ValueCountFrequency (%)
White only, Non-Hispanic 186336
75.7%
Hispanic 22570
 
9.2%
Black only, Non-Hispanic 19330
 
7.9%
Other race only, Non-Hispanic 12205
 
5.0%
Multiracial, Non-Hispanic 5581
 
2.3%

Length

2024-04-16T16:56:16.025354image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:16.154242image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
non-hispanic 223452
31.9%
only 217871
31.1%
white 186336
26.6%
hispanic 22570
 
3.2%
black 19330
 
2.8%
other 12205
 
1.7%
race 12205
 
1.7%
multiracial 5581
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i 689542
 
12.3%
n 687345
 
12.3%
453528
 
8.1%
o 441323
 
7.9%
a 288719
 
5.1%
c 283138
 
5.0%
l 248363
 
4.4%
H 246022
 
4.4%
s 246022
 
4.4%
p 246022
 
4.4%
Other values (14) 1779990
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5610014
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 689542
 
12.3%
n 687345
 
12.3%
453528
 
8.1%
o 441323
 
7.9%
a 288719
 
5.1%
c 283138
 
5.0%
l 248363
 
4.4%
H 246022
 
4.4%
s 246022
 
4.4%
p 246022
 
4.4%
Other values (14) 1779990
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5610014
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 689542
 
12.3%
n 687345
 
12.3%
453528
 
8.1%
o 441323
 
7.9%
a 288719
 
5.1%
c 283138
 
5.0%
l 248363
 
4.4%
H 246022
 
4.4%
s 246022
 
4.4%
p 246022
 
4.4%
Other values (14) 1779990
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5610014
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 689542
 
12.3%
n 687345
 
12.3%
453528
 
8.1%
o 441323
 
7.9%
a 288719
 
5.1%
c 283138
 
5.0%
l 248363
 
4.4%
H 246022
 
4.4%
s 246022
 
4.4%
p 246022
 
4.4%
Other values (14) 1779990
31.7%

AgeCategory
Categorical

Distinct13
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
Age 65 to 69
28557 
Age 60 to 64
26720 
Age 70 to 74
25739 
Age 55 to 59
22224 
Age 50 to 54
19913 
Other values (8)
122869 

Length

Max length15
Median length12
Mean length12.217249
Min length12

Characters and Unicode

Total characters3005712
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAge 65 to 69
2nd rowAge 70 to 74
3rd rowAge 75 to 79
4th rowAge 80 or older
5th rowAge 80 or older

Common Values

ValueCountFrequency (%)
Age 65 to 69 28557
11.6%
Age 60 to 64 26720
10.9%
Age 70 to 74 25739
10.5%
Age 55 to 59 22224
9.0%
Age 50 to 54 19913
8.1%
Age 75 to 79 18136
7.4%
Age 80 or older 17816
7.2%
Age 40 to 44 16973
6.9%
Age 45 to 49 16753
6.8%
Age 35 to 39 15614
6.3%
Other values (3) 37577
15.3%

Length

2024-04-16T16:56:16.307507image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
age 246022
25.0%
to 228206
23.2%
69 28557
 
2.9%
65 28557
 
2.9%
60 26720
 
2.7%
64 26720
 
2.7%
70 25739
 
2.6%
74 25739
 
2.6%
55 22224
 
2.3%
59 22224
 
2.3%
Other values (19) 303380
30.8%

Most occurring characters

ValueCountFrequency (%)
738066
24.6%
e 263838
 
8.8%
o 263838
 
8.8%
A 246022
 
8.2%
g 246022
 
8.2%
t 228206
 
7.6%
5 196667
 
6.5%
4 183265
 
6.1%
0 120507
 
4.0%
9 112393
 
3.7%
Other values (9) 406888
13.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3005712
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
738066
24.6%
e 263838
 
8.8%
o 263838
 
8.8%
A 246022
 
8.2%
g 246022
 
8.2%
t 228206
 
7.6%
5 196667
 
6.5%
4 183265
 
6.1%
0 120507
 
4.0%
9 112393
 
3.7%
Other values (9) 406888
13.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3005712
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
738066
24.6%
e 263838
 
8.8%
o 263838
 
8.8%
A 246022
 
8.2%
g 246022
 
8.2%
t 228206
 
7.6%
5 196667
 
6.5%
4 183265
 
6.1%
0 120507
 
4.0%
9 112393
 
3.7%
Other values (9) 406888
13.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3005712
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
738066
24.6%
e 263838
 
8.8%
o 263838
 
8.8%
A 246022
 
8.2%
g 246022
 
8.2%
t 228206
 
7.6%
5 196667
 
6.5%
4 183265
 
6.1%
0 120507
 
4.0%
9 112393
 
3.7%
Other values (9) 406888
13.5%

HeightInMeters
Real number (ℝ)

Distinct101
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7051504
Minimum0.91
Maximum2.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:16.454354image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum0.91
5-th percentile1.55
Q11.63
median1.7
Q31.78
95-th percentile1.88
Maximum2.41
Range1.5
Interquartile range (IQR)0.15

Descriptive statistics

Standard deviation0.10665407
Coefficient of variation (CV)0.062548188
Kurtosis0.0073722906
Mean1.7051504
Median Absolute Deviation (MAD)0.08
Skewness0.031680579
Sum419504.52
Variance0.011375091
MonotonicityNot monotonic
2024-04-16T16:56:16.619004image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.68 21694
 
8.8%
1.63 20835
 
8.5%
1.7 20054
 
8.2%
1.78 19540
 
7.9%
1.65 18825
 
7.7%
1.73 18504
 
7.5%
1.75 17441
 
7.1%
1.83 16936
 
6.9%
1.6 16487
 
6.7%
1.57 15534
 
6.3%
Other values (91) 60172
24.5%
ValueCountFrequency (%)
0.91 6
 
< 0.1%
0.95 1
 
< 0.1%
0.97 3
 
< 0.1%
1 2
 
< 0.1%
1.02 1
 
< 0.1%
1.03 1
 
< 0.1%
1.04 12
< 0.1%
1.05 17
< 0.1%
1.07 4
 
< 0.1%
1.08 1
 
< 0.1%
ValueCountFrequency (%)
2.41 2
 
< 0.1%
2.36 1
 
< 0.1%
2.34 1
 
< 0.1%
2.29 2
 
< 0.1%
2.26 6
 
< 0.1%
2.24 1
 
< 0.1%
2.21 1
 
< 0.1%
2.18 4
 
< 0.1%
2.16 6
 
< 0.1%
2.13 15
< 0.1%

WeightInKilograms
Real number (ℝ)

Distinct516
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.615179
Minimum28.12
Maximum292.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:16.820860image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum28.12
5-th percentile54.43
Q168.04
median81.65
Q395.25
95-th percentile122.47
Maximum292.57
Range264.45
Interquartile range (IQR)27.21

Descriptive statistics

Standard deviation21.323156
Coefficient of variation (CV)0.25501538
Kurtosis2.3372781
Mean83.615179
Median Absolute Deviation (MAD)13.61
Skewness1.0249895
Sum20571174
Variance454.67699
MonotonicityNot monotonic
2024-04-16T16:56:17.000325image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90.72 13066
 
5.3%
81.65 12018
 
4.9%
68.04 10365
 
4.2%
72.57 10350
 
4.2%
77.11 9725
 
4.0%
86.18 8808
 
3.6%
63.5 7570
 
3.1%
79.38 7229
 
2.9%
99.79 6818
 
2.8%
74.84 6593
 
2.7%
Other values (506) 153480
62.4%
ValueCountFrequency (%)
28.12 1
 
< 0.1%
29.48 2
 
< 0.1%
30.39 1
 
< 0.1%
30.84 3
 
< 0.1%
31.75 7
< 0.1%
32 1
 
< 0.1%
32.21 2
 
< 0.1%
33.57 3
 
< 0.1%
34.02 12
< 0.1%
34.47 4
 
< 0.1%
ValueCountFrequency (%)
292.57 1
< 0.1%
276.24 1
< 0.1%
273.52 1
< 0.1%
273.06 1
< 0.1%
272.16 2
< 0.1%
265 1
< 0.1%
263.08 2
< 0.1%
256.28 1
< 0.1%
254.01 1
< 0.1%
250.38 1
< 0.1%

BMI
Real number (ℝ)

Distinct3514
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.668136
Minimum12.02
Maximum97.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 MiB
2024-04-16T16:56:17.265270image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Quantile statistics

Minimum12.02
5-th percentile20.34
Q124.27
median27.46
Q331.89
95-th percentile40.72
Maximum97.65
Range85.63
Interquartile range (IQR)7.62

Descriptive statistics

Standard deviation6.5139735
Coefficient of variation (CV)0.22721999
Kurtosis3.8980498
Mean28.668136
Median Absolute Deviation (MAD)3.73
Skewness1.3264962
Sum7052992.1
Variance42.43185
MonotonicityNot monotonic
2024-04-16T16:56:17.428898image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
26.63 2727
 
1.1%
27.46 2040
 
0.8%
27.44 1964
 
0.8%
24.41 1922
 
0.8%
27.12 1893
 
0.8%
25.1 1650
 
0.7%
32.28 1526
 
0.6%
29.53 1453
 
0.6%
28.7 1432
 
0.6%
25.84 1415
 
0.6%
Other values (3504) 228000
92.7%
ValueCountFrequency (%)
12.02 1
< 0.1%
12.05 1
< 0.1%
12.11 2
< 0.1%
12.16 2
< 0.1%
12.27 2
< 0.1%
12.34 1
< 0.1%
12.36 1
< 0.1%
12.4 1
< 0.1%
12.44 1
< 0.1%
12.48 1
< 0.1%
ValueCountFrequency (%)
97.65 3
< 0.1%
97.43 1
 
< 0.1%
96.2 1
 
< 0.1%
95.66 1
 
< 0.1%
94.66 1
 
< 0.1%
92.73 1
 
< 0.1%
92.01 1
 
< 0.1%
91.72 1
 
< 0.1%
91.55 1
 
< 0.1%
88.77 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
True
135307 
False
110715 
ValueCountFrequency (%)
True 135307
55.0%
False 110715
45.0%
2024-04-16T16:56:17.551463image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

HIVTesting
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
161520 
True
84502 
ValueCountFrequency (%)
False 161520
65.7%
True 84502
34.3%
2024-04-16T16:56:17.665580image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
True
131196 
False
114826 
ValueCountFrequency (%)
True 131196
53.3%
False 114826
46.7%
2024-04-16T16:56:17.767492image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
146130 
True
99892 
ValueCountFrequency (%)
False 146130
59.4%
True 99892
40.6%
2024-04-16T16:56:17.867078image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
No, did not receive any tetanus shot in the past 10 years
81747 
Yes, received tetanus shot but not sure what type
74119 
Yes, received Tdap
70286 
Yes, received tetanus shot, but not Tdap
19870 

Length

Max length57
Median length49
Mean length42.074928
Min length18

Characters and Unicode

Total characters10351358
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowYes, received Tdap
2nd rowYes, received tetanus shot but not sure what type
3rd rowNo, did not receive any tetanus shot in the past 10 years
4th rowNo, did not receive any tetanus shot in the past 10 years
5th rowNo, did not receive any tetanus shot in the past 10 years

Common Values

ValueCountFrequency (%)
No, did not receive any tetanus shot in the past 10 years 81747
33.2%
Yes, received tetanus shot but not sure what type 74119
30.1%
Yes, received Tdap 70286
28.6%
Yes, received tetanus shot, but not Tdap 19870
 
8.1%

Length

2024-04-16T16:56:18.006371image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:18.145507image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
not 175736
 
8.8%
tetanus 175736
 
8.8%
shot 175736
 
8.8%
received 164275
 
8.2%
yes 164275
 
8.2%
but 93989
 
4.7%
tdap 90156
 
4.5%
10 81747
 
4.1%
years 81747
 
4.1%
no 81747
 
4.1%
Other values (9) 712839
35.7%

Most occurring characters

ValueCountFrequency (%)
1751961
16.9%
e 1389809
13.4%
t 1108665
10.7%
s 753360
 
7.3%
a 585252
 
5.7%
n 514966
 
5.0%
o 433219
 
4.2%
d 417925
 
4.0%
i 409516
 
4.0%
r 401888
 
3.9%
Other values (14) 2584797
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10351358
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1751961
16.9%
e 1389809
13.4%
t 1108665
10.7%
s 753360
 
7.3%
a 585252
 
5.7%
n 514966
 
5.0%
o 433219
 
4.2%
d 417925
 
4.0%
i 409516
 
4.0%
r 401888
 
3.9%
Other values (14) 2584797
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10351358
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1751961
16.9%
e 1389809
13.4%
t 1108665
10.7%
s 753360
 
7.3%
a 585252
 
5.7%
n 514966
 
5.0%
o 433219
 
4.2%
d 417925
 
4.0%
i 409516
 
4.0%
r 401888
 
3.9%
Other values (14) 2584797
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10351358
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1751961
16.9%
e 1389809
13.4%
t 1108665
10.7%
s 753360
 
7.3%
a 585252
 
5.7%
n 514966
 
5.0%
o 433219
 
4.2%
d 417925
 
4.0%
i 409516
 
4.0%
r 401888
 
3.9%
Other values (14) 2584797
25.0%

HighRiskLastYear
Boolean

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size240.4 KiB
False
235446 
True
 
10576
ValueCountFrequency (%)
False 235446
95.7%
True 10576
 
4.3%
2024-04-16T16:56:18.277037image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

CovidPos
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
No
167306 
Yes
70324 
Tested positive using home test without a health professional
 
8392

Length

Max length61
Median length2
Mean length4.2983798
Min length2

Characters and Unicode

Total characters1057496
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo

Common Values

ValueCountFrequency (%)
No 167306
68.0%
Yes 70324
28.6%
Tested positive using home test without a health professional 8392
 
3.4%

Length

2024-04-16T16:56:18.404404image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T16:56:18.529707image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
ValueCountFrequency (%)
no 167306
53.4%
yes 70324
22.5%
tested 8392
 
2.7%
positive 8392
 
2.7%
using 8392
 
2.7%
home 8392
 
2.7%
test 8392
 
2.7%
without 8392
 
2.7%
a 8392
 
2.7%
health 8392
 
2.7%

Most occurring characters

ValueCountFrequency (%)
o 209266
19.8%
N 167306
15.8%
e 129068
12.2%
s 120676
11.4%
Y 70324
 
6.7%
67136
 
6.3%
t 58744
 
5.6%
i 41960
 
4.0%
h 33568
 
3.2%
a 25176
 
2.4%
Other values (12) 134272
12.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1057496
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 209266
19.8%
N 167306
15.8%
e 129068
12.2%
s 120676
11.4%
Y 70324
 
6.7%
67136
 
6.3%
t 58744
 
5.6%
i 41960
 
4.0%
h 33568
 
3.2%
a 25176
 
2.4%
Other values (12) 134272
12.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1057496
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 209266
19.8%
N 167306
15.8%
e 129068
12.2%
s 120676
11.4%
Y 70324
 
6.7%
67136
 
6.3%
t 58744
 
5.6%
i 41960
 
4.0%
h 33568
 
3.2%
a 25176
 
2.4%
Other values (12) 134272
12.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1057496
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 209266
19.8%
N 167306
15.8%
e 129068
12.2%
s 120676
11.4%
Y 70324
 
6.7%
67136
 
6.3%
t 58744
 
5.6%
i 41960
 
4.0%
h 33568
 
3.2%
a 25176
 
2.4%
Other values (12) 134272
12.7%

Interactions

2024-04-16T16:56:05.409194image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:55:59.951820image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:01.126498image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:02.196051image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:03.255867image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:04.364311image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:05.585371image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:00.228515image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:01.305743image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:02.364428image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:03.429545image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:04.535246image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:05.845036image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:00.386833image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:01.477665image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:02.554075image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:03.611877image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:04.728440image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:06.023174image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:00.565839image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:01.674405image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:02.736464image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:03.812056image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:04.905693image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:06.215873image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:00.778664image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:01.855781image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:02.904178image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:04.004080image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:05.081297image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:06.385080image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:00.947102image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:02.025288image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:03.083739image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:04.186055image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
2024-04-16T16:56:05.249882image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/

Missing values

2024-04-16T16:56:07.045457image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-16T16:56:08.418461image/svg+xmlMatplotlib v3.8.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

StateSexGeneralHealthPhysicalHealthDaysMentalHealthDaysLastCheckupTimePhysicalActivitiesSleepHoursRemovedTeethHadHeartAttackHadAnginaHadStrokeHadAsthmaHadSkinCancerHadCOPDHadDepressiveDisorderHadKidneyDiseaseHadArthritisHadDiabetesDeafOrHardOfHearingBlindOrVisionDifficultyDifficultyConcentratingDifficultyWalkingDifficultyDressingBathingDifficultyErrandsSmokerStatusECigaretteUsageChestScanRaceEthnicityCategoryAgeCategoryHeightInMetersWeightInKilogramsBMIAlcoholDrinkersHIVTestingFluVaxLast12PneumoVaxEverTetanusLast10TdapHighRiskLastYearCovidPos
0AlabamaFemaleVery good4.00.0Within past year (anytime less than 12 months ago)Yes9.0None of themNoNoNoNoNoNoNoNoYesNoNoNoNoNoNoNoFormer smokerNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 65 to 691.6071.6727.99NoNoYesYesYes, received TdapNoNo
1AlabamaMaleVery good0.00.0Within past year (anytime less than 12 months ago)Yes6.0None of themNoNoNoNoNoNoNoNoYesYesNoNoNoNoNoNoFormer smokerNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 70 to 741.7895.2530.13NoNoYesYesYes, received tetanus shot but not sure what typeNoNo
2AlabamaMaleVery good0.00.0Within past year (anytime less than 12 months ago)No8.06 or more, but not allNoNoNoNoNoNoNoNoYesNoNoYesNoYesNoNoFormer smokerNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 75 to 791.85108.8631.66YesNoNoYesNo, did not receive any tetanus shot in the past 10 yearsNoYes
3AlabamaFemaleFair5.00.0Within past year (anytime less than 12 months ago)Yes9.0None of themNoNoNoNoYesNoYesNoYesNoNoNoNoYesNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 80 or older1.7090.7231.32NoNoYesYesNo, did not receive any tetanus shot in the past 10 yearsNoYes
4AlabamaFemaleGood3.015.0Within past year (anytime less than 12 months ago)Yes5.01 to 5NoNoNoNoNoNoNoNoYesNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 80 or older1.5579.3833.07NoNoYesYesNo, did not receive any tetanus shot in the past 10 yearsNoNo
5AlabamaMaleGood0.00.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 50 to 541.85120.2034.96YesYesYesNoYes, received tetanus shot but not sure what typeNoNo
6AlabamaFemaleGood3.00.0Within past year (anytime less than 12 months ago)Yes8.06 or more, but not allNoNoYesNoNoNoNoNoNoYesNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeYesBlack only, Non-HispanicAge 80 or older1.6388.0033.30NoNoYesYesNo, did not receive any tetanus shot in the past 10 yearsNoNo
7AlabamaMaleFair5.00.0Within past year (anytime less than 12 months ago)Yes8.01 to 5YesYesNoNoYesNoNoNoYesYesNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 75 to 791.7574.8424.37NoYesYesYesNo, did not receive any tetanus shot in the past 10 yearsNoYes
8AlabamaMaleGood2.00.05 or more years agoNo6.0None of themNoNoNoNoNoNoNoNoYesNoYesNoNoNoNoNoFormer smokerNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 40 to 441.7078.0226.94NoNoNoNoNo, did not receive any tetanus shot in the past 10 yearsNoYes
9AlabamaFemaleVery good0.00.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoYesYesNoNoNoYesNoNoNoNoNoNoNoFormer smokerNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 75 to 791.6863.5022.60NoNoYesYesNo, did not receive any tetanus shot in the past 10 yearsNoNo
StateSexGeneralHealthPhysicalHealthDaysMentalHealthDaysLastCheckupTimePhysicalActivitiesSleepHoursRemovedTeethHadHeartAttackHadAnginaHadStrokeHadAsthmaHadSkinCancerHadCOPDHadDepressiveDisorderHadKidneyDiseaseHadArthritisHadDiabetesDeafOrHardOfHearingBlindOrVisionDifficultyDifficultyConcentratingDifficultyWalkingDifficultyDressingBathingDifficultyErrandsSmokerStatusECigaretteUsageChestScanRaceEthnicityCategoryAgeCategoryHeightInMetersWeightInKilogramsBMIAlcoholDrinkersHIVTestingFluVaxLast12PneumoVaxEverTetanusLast10TdapHighRiskLastYearCovidPos
246012Virgin IslandsMaleFair7.030.0Within past year (anytime less than 12 months ago)No4.0None of themYesYesNoNoNoNoNoNoNoNoYesNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeYesBlack only, Non-HispanicAge 65 to 691.88117.9333.38YesYesNoNoNo, did not receive any tetanus shot in the past 10 yearsNoYes
246013Virgin IslandsMaleExcellent0.07.0Within past year (anytime less than 12 months ago)No4.0None of themNoNoNoNoNoNoYesNoNoYesNoNoYesNoNoYesNever smokedNot at all (right now)NoBlack only, Non-HispanicAge 18 to 241.6549.9018.30YesNoNoNoNo, did not receive any tetanus shot in the past 10 yearsNoNo
246014Virgin IslandsFemaleGood0.00.0Within past year (anytime less than 12 months ago)Yes12.01 to 5NoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoBlack only, Non-HispanicAge 65 to 691.6552.1619.14NoNoNoYesYes, received TdapNoNo
246015Virgin IslandsFemaleVery good0.00.0Within past year (anytime less than 12 months ago)Yes7.01 to 5NoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoBlack only, Non-HispanicAge 45 to 491.6577.1128.29YesYesNoNoNo, did not receive any tetanus shot in the past 10 yearsNoNo
246016Virgin IslandsMaleGood0.00.0Within past year (anytime less than 12 months ago)No6.01 to 5YesNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoCurrent smoker - now smokes every dayNever used e-cigarettes in my entire lifeYesBlack only, Non-HispanicAge 55 to 591.80118.8436.54YesYesYesNoYes, received tetanus shot but not sure what typeNoNo
246017Virgin IslandsMaleVery good0.00.0Within past 2 years (1 year but less than 2 years ago)Yes6.0None of themNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 60 to 641.78102.0632.28YesNoNoNoYes, received tetanus shot but not sure what typeNoNo
246018Virgin IslandsFemaleFair0.07.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoNoNoYesNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoBlack only, Non-HispanicAge 25 to 291.9390.7224.34NoNoNoNoNo, did not receive any tetanus shot in the past 10 yearsNoYes
246019Virgin IslandsMaleGood0.015.0Within past year (anytime less than 12 months ago)Yes7.01 to 5NoNoYesNoNoNoNoNoYesYesNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoMultiracial, Non-HispanicAge 65 to 691.6883.9129.86YesYesYesYesYes, received tetanus shot but not sure what typeNoYes
246020Virgin IslandsFemaleExcellent2.02.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoBlack only, Non-HispanicAge 50 to 541.7083.0128.66NoYesYesNoYes, received tetanus shot but not sure what typeNoNo
246021Virgin IslandsMaleVery good0.00.0Within past year (anytime less than 12 months ago)No5.0None of themYesNoNoYesNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeYesBlack only, Non-HispanicAge 70 to 741.83108.8632.55NoYesYesYesNo, did not receive any tetanus shot in the past 10 yearsNoYes

Duplicate rows

Most frequently occurring

StateSexGeneralHealthPhysicalHealthDaysMentalHealthDaysLastCheckupTimePhysicalActivitiesSleepHoursRemovedTeethHadHeartAttackHadAnginaHadStrokeHadAsthmaHadSkinCancerHadCOPDHadDepressiveDisorderHadKidneyDiseaseHadArthritisHadDiabetesDeafOrHardOfHearingBlindOrVisionDifficultyDifficultyConcentratingDifficultyWalkingDifficultyDressingBathingDifficultyErrandsSmokerStatusECigaretteUsageChestScanRaceEthnicityCategoryAgeCategoryHeightInMetersWeightInKilogramsBMIAlcoholDrinkersHIVTestingFluVaxLast12PneumoVaxEverTetanusLast10TdapHighRiskLastYearCovidPos# duplicates
0ArizonaFemaleExcellent0.00.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoYesNoNoNoYesNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 75 to 791.6356.7021.46YesNoYesYesYes, received TdapNoNo2
1MarylandFemaleGood0.00.0Within past year (anytime less than 12 months ago)Yes8.0None of themNoNoNoYesNoNoNoNoNoNoNoNoNoNoNoNoFormer smokerNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 65 to 691.6545.3616.64YesNoYesYesYes, received TdapNoNo2
2MarylandMaleExcellent0.00.0Within past year (anytime less than 12 months ago)Yes8.0None of themNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 50 to 541.7565.7721.41YesNoYesYesYes, received TdapNoNo2
3New JerseyMaleGood0.00.0Within past year (anytime less than 12 months ago)No8.06 or more, but not allNoNoYesNoNoNoNoNoNoYesNoNoNoNoNoNoFormer smokerNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 75 to 791.6380.7430.55YesNoNoNoNo, did not receive any tetanus shot in the past 10 yearsNoNo2
4Rhode IslandFemaleVery good0.00.0Within past year (anytime less than 12 months ago)Yes7.01 to 5NoNoNoYesNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 75 to 791.5768.0427.44YesNoYesYesNo, did not receive any tetanus shot in the past 10 yearsNoNo2
5South DakotaFemaleFair30.00.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoNoNoNoNoNoYesNoNoNoYesNoNoNever smokedNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 70 to 741.7590.7229.53NoNoYesYesNo, did not receive any tetanus shot in the past 10 yearsNoNo2
6VermontFemaleVery good0.00.0Within past year (anytime less than 12 months ago)Yes9.0None of themNoNoNoNoNoNoNoNoYesNoNoNoNoYesNoNoFormer smokerNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 70 to 741.6579.3829.12YesNoYesYesYes, received tetanus shot but not sure what typeNoNo2
7WashingtonMaleExcellent0.00.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoYesNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeNoWhite only, Non-HispanicAge 60 to 641.8077.1123.71YesYesYesNoYes, received TdapNoNo2
8WashingtonMaleVery good0.00.0Within past year (anytime less than 12 months ago)Yes7.0None of themNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNoNever smokedNever used e-cigarettes in my entire lifeYesWhite only, Non-HispanicAge 65 to 691.93104.3328.00YesYesYesYesNo, did not receive any tetanus shot in the past 10 yearsNoNo2